breve: a 3D environment for the simulation of decentralized systems and artificial life

BREVE is a 3D simulation environment designed for simulation of decentralized systems and artificial life. While breve is conceptually similar to existing packages such as Swarm and StarLogo, the implementation of BREVE-which simulates both continuous time and continuous 3D space-is quite different such that the environment is suited to a different class of simulations. BREVE includes an interpreted object oriented language; an OpenGL display engine; collision detection; as well as experimental support for articulated body physical simulation and collision resolution with static and dynamic friction. The ultimate goal of the system is to allow decentralized simulations to be implemented quickly and easily while providing a powerful framework to facilitate the construction of advanced artificial life simulations.

[1]  Master Gardener,et al.  Mathematical games: the fantastic combinations of john conway's new solitaire game "life , 1970 .

[2]  R. Featherstone The Calculation of Robot Dynamics Using Articulated-Body Inertias , 1983 .

[3]  Craig W. Reynolds Flocks, herds, and schools: a distributed behavioral model , 1987, SIGGRAPH.

[4]  Thomas S. Ray,et al.  Is It Alive or Is It GA? , 1991, ICGA.

[5]  T. Ray Evolution , Ecology and Optimization of Digital Organisms , 1992 .

[6]  Ming C. Lin,et al.  Efficient collision detection for animation and robotics , 1993 .

[7]  Piero Mussio,et al.  Toward a Practice of Autonomous Systems , 1994 .

[8]  Mitchel Resnick,et al.  Turtles, termites, and traffic jams - explorations in massively parallel microworlds , 1994 .

[9]  Karl Sims,et al.  Evolving 3d morphology and behavior by competition , 1994 .

[10]  C. Titus Brown,et al.  Evolutionary Learning in the 2D Artificial Life System "Avida" , 1994, adap-org/9405003.

[11]  K. Lindgren,et al.  Evolutionary dynamics of spatial games , 1994 .

[12]  Peter J. Angeline,et al.  Adaptive and Self-adaptive Evolutionary Computations , 1995 .

[13]  David J. Montana,et al.  Strongly Typed Genetic Programming , 1995, Evolutionary Computation.

[14]  David J. Montana,et al.  Evolving control laws for a network of traffic signals , 1996 .

[15]  Nelson Minar,et al.  The Swarm Simulation System: A Toolkit for Building Multi-Agent Simulations , 1996 .

[16]  Brian Mirtich,et al.  Impulse-based dynamic simulation of rigid body systems , 1996 .

[17]  Peter J. Angeline,et al.  Two self-adaptive crossover operators for genetic programming , 1996 .

[18]  A. N. Pargellis,et al.  The spontaneous generation of digital “Life” , 1996 .

[19]  John R. Koza,et al.  Genetic programming 1997 : proceedings of the Second Annual Conference, July 13-16, 1997, Stanford University , 1997 .

[20]  Wolfgang Banzhaf,et al.  Genetic Programming: An Introduction , 1997 .

[21]  L. Yaeger Computational Genetics, Physiology, Metabolism, Neural Systems, Learning, Vision, and Behavior or PolyWorld: Life in a New Context , 1997 .

[22]  A. Ruina,et al.  A New Algebraic Rigid-Body Collision Law Based on Impulse Space Considerations , 1998 .

[23]  Christopher R. Stephens,et al.  Self-Adaptation in Evolving Systems , 1997, Artificial Life.

[24]  Brian Mirtich,et al.  V-Clip: fast and robust polyhedral collision detection , 1998, TOGS.

[25]  Jordan B. Pollack,et al.  Automatic design and manufacture of robotic lifeforms , 2000, Nature.

[26]  L. Sander Diffusion-limited aggregation: A kinetic critical phenomenon? , 2000 .

[27]  W. Langdon,et al.  Autoconstructive Evolution : Push , PushGP , and Pushpop , 2001 .

[28]  William E. Hart,et al.  A Convergence Analysis of Unconstrained and Bound Constrained Evolutionary Pattern Search , 2001, Evolutionary Computation.

[29]  Terry Van Belle,et al.  Code Factoring And The Evolution Of Evolvability , 2002, GECCO.

[30]  Lee Spector,et al.  Genetic Programming and Autoconstructive Evolution with the Push Programming Language , 2002, Genetic Programming and Evolvable Machines.